{
 "cells": [
  {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "本次任务：\n",
    "    将采集的多个表格的数据字段整合到主播个人信息表(pht表)中，最终整合结果如下所示：\n",
    "![%E6%95%B0%E6%8D%AE%E5%AD%97%E6%AE%B5.png](attachment:%E6%95%B0%E6%8D%AE%E5%AD%97%E6%AE%B5.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# 导入包  \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.stats\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%config InlineBackend.figure_format = 'retina' # 设置图片清晰度\n",
    "plt.rcParams['font.sans-serif'] = ['Simsun']   # 指定默认字体 Simsun为宋体\n",
    "plt.rcParams['axes.unicode_minus'] = False     # 解决保存图像时负号‘-’显示为方块的问题\n",
    "\n",
    "from datetime import datetime\n",
    "import time, re\n",
    "\n",
    "pd.set_option('display.max_columns', None)    # 显示所有列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# pht表：主播id表\n",
    "pht = pd.read_csv('data\\用户id.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>用户id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
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      ],
      "text/plain": [
       "                用户id\n",
       "0         1820796294\n",
       "1         2183525275\n",
       "2         2334560814\n",
       "3         1016578758\n",
       "4         1018667693\n",
       "...              ...\n",
       "10956     2323517119\n",
       "10957  1279532989136\n",
       "10958     2214316071\n",
       "10959     1746647510\n",
       "10960      136907042\n",
       "\n",
       "[10961 rows x 1 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pht"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10961位主播的用户id。接下来将对其他表的字段整合到pht表中。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 周贡榜的信息合并"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "wc = pd.read_csv('data\\周贡献榜.csv')\n",
    "wc.用户id = wc.用户id.astype(int)\n",
    "# wc.drop(columns=['iSFFlag','sLogo','tNobleLevel'], inplace=True)   # 删除一些没有用信息的列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wc表共有45018条样本。\n"
     ]
    }
   ],
   "source": [
    "wc.head()\n",
    "print('wc表共有%s条样本。'%wc.shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "wc表的字段：  \n",
    "- lUid：打赏的用户id\n",
    "- 用户id：主播的id\n",
    "- iScore：打赏金额\n",
    "- iGuardLevel：开通的守护者等级，0表示未开通\n",
    "- iNobleLevel：贵族等级\n",
    "- iUserLevel：用户平台等级"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 主播吸金程度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "贡献榜总人数：主播当前贡献榜上的总用户数，由于数据获取的限制，最多只显示50名  \n",
    "<font color='#73BE71'>主播对用户打赏的吸金程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = wc.groupby('用户id').lUid.count().rename('贡献榜总人数').reset_index()\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "pht['贡献榜总人数'].fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "贡献榜总金额：主播当前贡献榜上总的贡献金额，单位：金豆  \n",
    "<font color='#73BE71'>主播吸金程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = wc.groupby('用户id').iScore.sum().rename('贡献榜总金额').reset_index()\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "pht['贡献榜总金额'].fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "是否有收入：主播当前贡献榜上是否存在贡献  \n",
    "<font color='#73BE71'>主播吸金程度</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 主播吸引打赏的用户群体的等级特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = wc.drop_duplicates('lUid').lUid.values\n",
    "pht['是否有收入'] = pht.用户id.isin(a).map({True:1, False:0})\n",
    "pht['是否有收入'] = pht.贡献榜总金额.apply(lambda x: 1 if x>0 else 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "贡献榜平均用户等级：主播当前贡献榜上的用户的平均等级，缺失值用-1填充，表示无贡献用户  \n",
    "<font color='#73BE71'>主播吸引打赏的用户群体的等级特征</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = wc.groupby('用户id').iUserLevel.mean().rename('贡献榜平均用户等级').reset_index()\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "pht['贡献榜平均用户等级'].fillna(0, inplace=True)   # 缺失值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "高等级用户数：主播当前贡献榜上的高等级用户数量（直播观看等级大于5的用户数量）  \n",
    "<font color='#73BE71'>主播吸引打赏的用户群体的等级特征</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "wc.loc[wc[wc.iUserLevel>16].index, '是否为高等级用户'] = 1\n",
    "a = wc.groupby('用户id').是否为高等级用户.sum().rename('高等级用户数')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "pht['高等级用户数'].fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "高等级用户数占比：主播当前贡献榜上的高等级用户的数量占比  \n",
    "<font color='#73BE71'>主播吸引打赏的用户群体的等级特征</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "pht['高等级用户数占比'] = (pht['高等级用户数']/pht['贡献榜总人数']).fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 主播吸引打赏的用户群体的财力情况"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "贵族数：主播当前贡献榜上的用户中贵族数量，缺失值用0填充  \n",
    "<font color='#73BE71'>主播吸引打赏的用户群体的财力情况</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "wc.loc[wc[wc.iNobleLevel==0].index , 'iNobleLevel'] = np.nan\n",
    "a = wc.groupby('用户id').iNobleLevel.count().rename('贵族数').reset_index()\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "pht['贵族数'].fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "金主数量：主播当前贡献榜上的金主数量（贡献排名TOP 5\\%的打赏用户为金主）  \n",
    "<font color='#73BE71'>主播吸引打赏的用户群体的财力情况</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = wc.iScore.sort_values(ascending=False)\n",
    "wc['是否金主'] = wc.index.isin(a[:int(len(a)/5)].index)\n",
    "wc['是否金主'] = wc['是否金主'].map({True:1, False:0})\n",
    "\n",
    "a = wc.groupby('用户id').是否金主.sum().rename('金主数量')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "pht['金主数量'].fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "贡献榜人均金额：主播当前贡献榜上的人均打赏金额，单位：金豆  \n",
    "<font color='#73BE71'>主播吸引打赏的用户群体的财力情况</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['贡献榜人均金额'] = (pht['贡献榜总金额']/pht['贡献榜总人数']).fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 主播吸引打赏的用户群体的专一程度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "广泛贡献用户数：主播当前贡献榜上的广泛贡献用户数  \n",
    "对5个以上主播打赏过的用户（由于数据爬取的时效性，这里有隐含条件：时间==7天内）。  \n",
    "<font color='#73BE71'>主播吸引打赏的用户群体的专一程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "      <td>1.0</td>\n",
       "      <td>https://huyaimg.msstatic.com/avatar/1006/95/fa...</td>\n",
       "      <td>25</td>\n",
       "      <td>{'iNobleLevel': 1, 'iAttrType': 0}</td>\n",
       "      <td>0</td>\n",
       "      <td>-2147483648</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45017</td>\n",
       "      <td>1279518128905</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>https://huyaimg.msstatic.com/avatar/1087/0c/25...</td>\n",
       "      <td>22</td>\n",
       "      <td>{'iNobleLevel': 2, 'iAttrType': 0}</td>\n",
       "      <td>0</td>\n",
       "      <td>-2147483648</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45018 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                lUid   iScore  iGuardLevel  iNobleLevel  \\\n",
       "0         1786502568  1941400            0          2.0   \n",
       "1      1199515156356  1798200            0          5.0   \n",
       "2         1698832695   657400            0          1.0   \n",
       "3         1356924630   503200            0          4.0   \n",
       "4      1199573401591   498000            0          1.0   \n",
       "...              ...      ...          ...          ...   \n",
       "45013     1464086656     5000            0          NaN   \n",
       "45014     1632134593     3700            0          NaN   \n",
       "45015     1707464702     1000            0          NaN   \n",
       "45016      880783781    33000            0          1.0   \n",
       "45017  1279518128905      100            0          2.0   \n",
       "\n",
       "                                                   sLogo  iUserLevel  \\\n",
       "0      https://huyaimg.msstatic.com/avatar/1033/6b/7a...          29   \n",
       "1      https://huyaimg.msstatic.com/avatar/1031/93/d0...          15   \n",
       "2      https://huyaimg.msstatic.com/avatar/1030/30/f1...          16   \n",
       "3      https://huyaimg.msstatic.com/avatar/1096/d6/cf...          19   \n",
       "4      https://huyaimg.msstatic.com/avatar/1075/5c/91...           2   \n",
       "...                                                  ...         ...   \n",
       "45013  http://huyaimg.msstatic.com/avatar/1060/f6/0b9...          10   \n",
       "45014  http://huyaimg.msstatic.com/avatar/1060/2a/572...           6   \n",
       "45015  https://huyaimg.msstatic.com/avatar/1075/26/e4...           5   \n",
       "45016  https://huyaimg.msstatic.com/avatar/1006/95/fa...          25   \n",
       "45017  https://huyaimg.msstatic.com/avatar/1087/0c/25...          22   \n",
       "\n",
       "                              tNobleLevel  iSFFlag        用户id  是否为高等级用户  是否金主  \n",
       "0      {'iNobleLevel': 2, 'iAttrType': 0}        0  1820796294       1.0     1  \n",
       "1      {'iNobleLevel': 5, 'iAttrType': 0}        0  1820796294       NaN     1  \n",
       "2      {'iNobleLevel': 1, 'iAttrType': 0}        0  1820796294       NaN     1  \n",
       "3      {'iNobleLevel': 4, 'iAttrType': 0}        0  1820796294       1.0     1  \n",
       "4      {'iNobleLevel': 1, 'iAttrType': 0}        0  1820796294       NaN     1  \n",
       "...                                   ...      ...         ...       ...   ...  \n",
       "45013  {'iNobleLevel': 0, 'iAttrType': 0}        0 -2147483648       NaN     0  \n",
       "45014  {'iNobleLevel': 0, 'iAttrType': 0}        0 -2147483648       NaN     0  \n",
       "45015  {'iNobleLevel': 0, 'iAttrType': 0}        0 -2147483648       NaN     0  \n",
       "45016  {'iNobleLevel': 1, 'iAttrType': 0}        0 -2147483648       1.0     0  \n",
       "45017  {'iNobleLevel': 2, 'iAttrType': 0}        0 -2147483648       1.0     0  \n",
       "\n",
       "[45018 rows x 11 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = wc.groupby('lUid').iScore.count(); a = a[a>3].index\n",
    "wc['是否为广泛贡献用户'] = wc.lUid.isin(a).map({True:1, False:0})\n",
    "a = wc.groupby('用户id').是否为广泛贡献用户.sum().rename('广泛贡献用户数').reset_index()\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "pht['广泛贡献用户数'].fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[守护者](https://blog.huya.com/product/639)个数：主播当前贡献榜上的守护者个数  \n",
    "> 贵族和守护者的区别：守护者比贵族更加侧重对主播专一的喜爱。因为守护者只在当前开通的直播间有牌面，而贵族在哪个直播间都有牌面。   \n",
    "\n",
    "<font color='#73BE71'>主播吸引打赏的用户群体对主播的专一程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "Guard_dict = wc.groupby('用户id').iGuardLevel.count().to_dict()\n",
    "pht['守护者个数'] = pht.用户id.map(Guard_dict)\n",
    "pht.守护者个数.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 视频动态的信息合并"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "iv = pd.read_csv('data\\视频动态.csv')\n",
    "iv.drop_duplicates(inplace=True)\n",
    "iv['cTime'] = iv.cTime.astype('datetime64')\n",
    "iv = iv.rename(columns={'uid':'用户id'})       # 重命名uid\n",
    "# 提取字段\n",
    "iv['观看次数'] = iv.videoInfo.apply(lambda x: eval(x)['videoPlayNum'])\n",
    "# 观看时长\n",
    "start_time = datetime.strptime('1900-1-1', '%Y-%m-%d')\n",
    "iv['视频时长'] = iv.videoInfo.apply(lambda x: eval(x)['videoDuration'])\n",
    "iv['视频时长'] = iv.视频时长.apply(lambda x: datetime.strptime(x, '%M:%S') if len(x)==5 else datetime.strptime(x, '%H:%M:%S'))\n",
    "iv['视频时长'] = iv.视频时长.apply(lambda x: (x - start_time).seconds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iv表共有27172条样本。\n"
     ]
    }
   ],
   "source": [
    "print('iv表共有%s条样本。'%iv.shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "iv表字段：  \n",
    "- 用户id：主播的id\n",
    "- title：视频标题\n",
    "- favorCount：点赞数  \n",
    "- commentCount：评论数\n",
    "- shareCount：分享数\n",
    "- comment：评论内容\n",
    "- cTime：发布时间\n",
    "- roomId：直播间id\n",
    "- 观看次数\n",
    "- 视频时长"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "视频平均时长  \n",
    "<font color='#73BE71'>主播视频的时长特点</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = iv.groupby('用户id').视频时长.mean().rename('视频平均时长')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "每周视频更新频率  \n",
    "<font color='#73BE71'>主播对视频动态的维护程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\software\\Anaconda3\\lib\\site-packages\\pandas\\core\\groupby\\groupby.py:1558: FutureWarning: how in .resample() is deprecated\n",
      "the new syntax is .resample(...).count()\n",
      "  return get_resampler_for_grouping(self, rule, *args, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "a = iv.groupby('用户id')[['cTime']].resample(rule='W', on='cTime', how='count').groupby(level=0).mean()  # 运行时间较长\n",
    "b = a.groupby(level=0).mean().rename(columns={'cTime':'视频平均每周更新频率'})\n",
    "pht = pd.merge(pht, b, on='用户id', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 视频的受欢迎程度  \n",
    "点赞、分享、收藏、评论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "视频平均点赞数  \n",
    "<font color='#73BE71'>视频的受欢迎程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = iv.groupby('用户id').favorCount.mean().rename('视频平均点赞数')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "视频平均评论数   \n",
    "<font color='#73BE71'>视频的受欢迎程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = iv.groupby('用户id').commentCount.mean().rename('视频平均评论数')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "视频平均分享数   \n",
    "<font color='#73BE71'>视频的受欢迎程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = iv.groupby('用户id').shareCount.mean().rename('视频平均分享数')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "视频平均观看次数  \n",
    "<font color='#73BE71'>视频的受欢迎程度</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = iv.groupby('用户id').观看次数.mean().rename('视频平均观看次数')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对有关视频的字段进行缺失值填充，填充为0，即没有发布视频的主播就没有视频相关的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht.loc[:, '视频平均时长': '视频平均观看次数'] = pht.loc[:, '视频平均时长': '视频平均观看次数'].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 公会信息合并"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "channel = pd.read_csv('data\\用户id-公会数据.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "channel表字段：\n",
    "- 用户id：主播的id\n",
    "- isPlaintum：是否加入公会\n",
    "- channelID：公会id\n",
    "- name：公会名称\n",
    "- isDiamond：是否为钻石公会"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "channel表共有11145条样本。\n"
     ]
    }
   ],
   "source": [
    "print('channel表共有%s条样本。'%channel.shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "是否为钻石公会：True：钻石，False：白金，NaN：无公会  \n",
    "<font color='#73BE71'>主播所在的公会等级情况</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "pht = pd.merge(pht, channel[['用户id', 'isDiamond']], on='用户id', how='left')\n",
    "pht.rename(columns={'isDiamond':'是否为钻石公会'}, inplace=True)\n",
    "pht['是否为钻石公会'] = pht.是否为钻石公会.map({True:'钻石', False:'白金'})\n",
    "pht['是否为钻石公会'].fillna('无', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "公会规模：主播所在的公会规模大小，在channel表出现大于100位主播的公会为大规模，20-100位主播的公会为中等规模，0-20位主播的公会为小规模，`无`表示没有入公会。  \n",
    "<font color='#73BE71'>主播所在的公会规模</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "a = channel.channelId.value_counts()\n",
    "bins = [-1, 20, 100, 1000]; labels = ['小', '中', '大']\n",
    "channel_size_dic = pd.cut(a, bins=bins, labels=labels).to_dict()\n",
    "channel['公会规模'] = channel.channelId.map(channel_size_dic)\n",
    "pht = pd.merge(pht, channel[['用户id','公会规模']], on='用户id')\n",
    "pht['公会规模'].fillna('无', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将以上整理为“公会概况”  \n",
    "将指标拆解为哑变量：大规模钻石公会、中规模钻石公会、小规模钻石公会、大规模白金公会、中规模白金公会、小规模白金公会、无公会。  \n",
    "<font color='#73BE71'>反映主播所在公会的等级情况和规模</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['公会概况'] = pht[['是否为钻石公会','公会规模']].apply(lambda x: x[0]+x[1]+'规模公会' if x[0]!='无' else '无公会', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "无公会        4705\n",
       "白金小规模公会    2691\n",
       "白金中规模公会    2238\n",
       "钻石中规模公会     738\n",
       "钻石小规模公会     446\n",
       "钻石大规模公会     143\n",
       "Name: 公会概况, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据概况\n",
    "pht.公会概况.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 本次开播信息合并 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ht表：每隔半小时爬取一次英雄联盟直播专区的在播情况，包括直播主标题，当前总人气，直播间推荐标签，是否有蓝光功能，蓝光清晰度等信息。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "ht = pd.read_csv(r'data\\4月4日数据.csv')\n",
    "ht.fillna(method='bfill', inplace=True)        # 填充抓取时间的缺失值\n",
    "ht['get_time'] = ht.get_time.map(time.localtime).map(lambda x: time.strftime(\"%Y--%m--%d %H:%M:%S\", x)).astype('datetime64')  # 时间戳转日期格式\n",
    "ht = ht.rename(columns={'uid':'用户id'})        # 重命名列名"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ht表的字段：\n",
    "- 用户id：主播id\n",
    "- get_time：该条信息获取时间\n",
    "- totalCount：当前总人气\n",
    "- roomName：直播间标题\n",
    "- recommendStatus：房间推荐状态\n",
    "- isBluRay：是否有蓝光\n",
    "- bluRayMBitRate：蓝光分辨率\n",
    "- liveSourceType：直播类型（官方赛事、直播回放等）\n",
    "- attribute：标签内容（英雄名、大神推荐、魅力新星等）\n",
    "- profileRoom：直播间id\n",
    "- isRoomPay：是否为付费观看"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ht表的`attribute`字段解析：\n",
    "- ListPos2字典存储的是英雄名\n",
    "- ListPos1字典存储的是直播推荐标签"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 主播的平均开播人气  \n",
    "主播当天被记录下来的人气的平均值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = ht.groupby('用户id').totalCount.mean().sort_values().rename('平均人气').reset_index()\n",
    "pht = pd.merge(a, pht, on='用户id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22b71698d48>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 247,
       "width": 394
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pht.平均人气.hist()   # 查看直方图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "因为数据记录异常（爬不到人气值），人气值会被误记为0，且大主播的背后往往有财力的支持，人气影响因素受到机器人粉丝等其他影响，无法反应真正的受欢迎程度。所以对过高(Q1-1.5IQR)或过低(Q2-1.5IQR)的数据做删除处理。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22b750dff88>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 247,
       "width": 387
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "describe = pht.平均人气.describe(percentiles=[0.05, 0.25, 0.75, 0.95])\n",
    "IQR = describe['75%'] - describe['25%']\n",
    "下边缘 = describe['25%'] - 1.5 * IQR\n",
    "上边缘 = describe['75%'] + 1.5 * IQR\n",
    "\n",
    "pht[(pht.平均人气>下边缘)&(pht.平均人气<上边缘)].平均人气.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht = pht[(pht.平均人气>下边缘)&(pht.平均人气<上边缘)]   # 剔除异常值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "去除了1758(15.7\\%)条数据，还剩9387条数据。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 英雄数量\n",
    "    1. 玩过几个英雄  \n",
    "    2. 是否为热门英雄 + 英雄位置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 当前玩的英雄\n",
    "ht['attribute'].fillna('', inplace=True)                                                 # 填充缺失值\n",
    "ht['英雄'] = ht['attribute'].apply(lambda x: re.findall(\"2': {'sContent': '(.*?)'\", x))  # 提取ListPos2的sContent标签，即英雄\n",
    "ht['英雄'] = ht['英雄'].apply(lambda x: x[0] if len(x)>0 else np.nan)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 1. 玩过几个英雄"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "LegCount_dict = ht.drop_duplicates(subset=['用户id', '英雄']).groupby('用户id').英雄.count().to_dict()\n",
    "pht['英雄个数'] = pht.用户id.map(LegCount_dict)\n",
    "pht.英雄个数.fillna(pht.英雄个数.mean(), inplace=True)           # 用均值填充缺失值，均值 = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 2.  英雄概况 = 是否为热门英雄 + 英雄位置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# 当前玩的英雄位置--'上单', '打野', '辅助', '下路', '中单'\n",
    "with open('data\\英雄位置字典.txt', 'r', encoding='utf-8') as f:\n",
    "    position = eval(f.read())\n",
    "\n",
    "ht['英雄位置'] = ht.英雄.map(position)\n",
    "ht['英雄位置'] = ht['英雄位置'].fillna('未知')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "ht['当前标签'] = ht['attribute'].apply(lambda x: re.findall(\"1': {'sContent': '(.*?)'\", x)) # [上电视]、[大神推荐]等\n",
    "ht['当前标签'] = ht['当前标签'].apply(lambda x: str(x)[1:-1])    # 去掉符号[]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "热门英雄的定义：ht表中出现频次最高的前十个英雄"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "hot_leg = ht.英雄.value_counts().sort_values(ascending=False).iloc[:10].index \n",
    "\n",
    "ht.loc[ht.英雄.isin(hot_leg), '热门英雄'] = '热门'\n",
    "ht.loc[(~ht.英雄.isna())&(~ht.英雄.isin(hot_leg)), '热门英雄'] = '非热门'\n",
    "ht['热门英雄'] = ht['热门英雄'].fillna('未知')     # 用字符串填充，后续需要以字符串类型和字段`英雄位置`相加"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于ht表中没有检测出过英雄的主播（22\\%）的数据，不做去除处理。  \n",
    "考虑到未知英雄在`热门英雄`和`英雄位置`字段会出现共线性，所以将两个字段做<u>交互处理</u>。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "先得到 热门+位置的字段，再对该字段`group by`，查看每个字段的人气值是否有显著不同。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "dic = {'未知未知': '未知'}\n",
    "ht['热门+位置'] = ht[['热门英雄','英雄位置']].sum(axis=1).apply(lambda x: dic.get(x, x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 缺点：\n",
    "1. 英雄位置只能进行传统的匹配（查字典匹配），一个英雄只对应一个位置，和事实有出入。    \n",
    "> 除此之外，还可以考虑版本强势英雄等。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于pht表中的一个主播，显示人气最高的时候的热门+位置，如果人气最高时的英雄是未知，那么找下一个人气最高时的热门+位置。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据提取思路：先将人气降序排序，然后去重用户id，保留第一个。提取{用户id: 热门+位置}的字典备用\n",
    "IDHot_dict = ht[~ht.英雄.isna()].sort_values('totalCount', ascending=False).drop_duplicates(['用户id']).set_index('用户id')['热门+位置'].to_dict()\n",
    "pht['英雄概况'] = pht.用户id.map(IDHot_dict)\n",
    "pht.英雄概况.fillna('未知', inplace=True)         # 填充缺失值为未知"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22b78c6ce88>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Rgketa39JkiSpL12dMhT1z38bhYGWs4HHACvr5UUT9t+otb2vdpIkSdLgdBUIbgYSuM+EbTcCW9U/bwO2ndBma+DKVvs+2kmSJEmD00kgyMyVwP8y+SLbTYFr6yMH5wC7T2izjOpIAn21kyRJkoaoy1mGTgL2iYjx6xaWAWfUz48H9oqI0Xn9RMRuwDbACa19+monSZIkDUqXgeDd9Z/3t6MVEbEd8FSqm4ABHAtcCBze2u8IYEVmXtpa11c7SZIkaVA6u1NxZl4XEU8EjoqIY6muK9gSeG5m/qRuc1dE7AO8PyJOBBYC5wNHjr1WL+0kSZKkoeksEABk5uXAfutoczNw0Hq8Vi/tJEmSpCHp8pQhSZIkSbOMgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKpiBQJIkSSqYgUCSJEkqmIFAkiRJKtiCvjsgSZo+Ox12Wt9d4PKj9u27C5KkDeARAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgC/rugKR7Z6fDTuu7CwBcftS+fXdBkiT9DjxCIEmSJBXMQCBJkiQVzEAgSZIkFay3awgi4j7AfwOHZuaZrfWbAyuATagCy4XAkZm5emz/XtpJkiRJQ9LnEYIjgGXtFRExHzgV+GVmvjAznw/sDBw9G9pJkiRJQ9PLEYKIeBJw1YRN+wN7AHu31r0TuCAiPpyZl/TcrhfOJiNJkqSZ0vkRgojYFHgJ8C8TNr8MOD0zbx2tyMyLgaupfmnvu50kSZI0KH2cMnQk8NbMzPbKiAhgT+BHE/a5BHhsn+3WJiLOnfRg7JQoSZIkabbpNBBExDOB8zLzygmblwJLqL6VH3c9sEPP7SRJkqTB6ewagojYGnh6Zr56iiYb1z9XTdi2Cljcc7spZebySevrowSPWtf+kiRJUl+6PEJwRP2Yysr656IJ2zZqbe+rnSRJkjQ4nRwhiIhdqL5pP6Q6ZX8NB0TEnsApwG3AthNeYmtgdJrRjT21kyRJkgank0CQmf8DHDy+PiLeBXxqdGOyiDgH2H3CSywDPlK/VvbRTpIkSRqiPm9MNsnxwF4RMTqvn4jYDdgGOGEWtJMkSZIGpbdAEBEL66cLW6uPBS4EDm+tOwJYkZmXzoJ2kiRJ0qD0cWOy+RHxJqpfwgHeHRFviYjNMvMuYB9g+4g4MSJOoroXwJvbr9FXO0mSJGloOpt2dCQzVwPvrRcPmLD9ZuCg9XidXtpJkiRJQzLbriGQJEmS1CEDgSRJklQwA4EkSZJUMAOBJEmSVDADgSRJklSwzmcZkn4XOx12Wt9dAODyo/btuwuSJEnTwiMEkiRJUsEMBJIkSVLBDASSJElSwQwEkiRJUsEMBJIkSVLBnGVI0pzn7FOSJN17HiGQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKZiCQJEmSCmYgkCRJkgpmIJAkSZIKtqCrPygilgP7ASuBrYBdgCMz86yxdpsDK4BNqALLhXW71bOhnSRJkjQknRwhiIgnAkcDb8nMIzLz1fXy1yPiIa1284FTgV9m5gsz8/nAznVb+m4nSZIkDU1Xpwy9CrgoM+8crcjMrwFXAQe02u0P7AG8rbXuncBrImLZLGgnSZIkDUpXgWAT4ICIiLH1NwFLW8svA07PzFtHKzLzYuBqql/a+24nSZIkDUqXRwienZk5WhERmwDLgO/VywHsCfxowv6XAI/ts50kSZI0RJ1cVJyZVwJXjq0+FLgcOLFeXgosofpWftz1wG49t5tSRJw7xSZPN5IkSdKs1tksQ20R8TDgIGDv1nUFG9c/V03YZRWwuOd2kiRJ0uB0HggiYmfgA8DTMvMXrU0r65+LJuy2UWt7X+2mlJnLJ62vjxw8al37S5IkSX3pNBDUYWAFsF9mXje2+UbgNmDbCbtuTXPKUV/tJEmSpMHp7E7FEbED8EHg5e0wEBE7AtQXHJ8D7D5h92XA2X22kyRJkoaoqxuTLQGOAQ7OzBta6+cDf91qejywV0Rs3GqzG7ANcMIsaCdJkiQNSldHCI4BPgYsiYhd6sdDgfdTna4zcixwIXB4a90RwIrMvHQWtJMkSZIGpatrCA6sH5O8fPQkM++KiH2A90fEicBC4HzgyPYOfbWTJEmShqar+xCM36F4bW1vppqSdFa2kyRJkoaks4uKJUmSJM0+BgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAL+u7AbBIRmwMrgE2owtKFwJGZubrXjkmSJEkzxCMEtYiYD5wK/DIzX5iZzwd2Bo7ut2eSJEnSzPEIQWN/YA9g79a6dwIXRMSHM/OSfrolSZIkzRyPEDReBpyembeOVmTmxcDVVGFBkiRJGhwDARARAewJ/GjC5kuAx3bbI0mSJKkbkZl996F3EbEVcD1waGZ+eGzbp4HdMvNha9n/3Ck2PWLx4sXzd91119+pfxf84le/0/7TZff7bd53F6xFi7VoWIvGbKjFbKgDWIs2a9GwFg1r0RhCLS6++GJuv/32GzNzqw3d10AARMSOwBXAKzPz42PbjgMen5m7rGX/qQLB7sCtwOXT1NV7a1n90+sgrEWbtWhYi4a1aFiLhrVoWIuGtWjMhlrsBNySmQ/c0B29qLiysv65aMK2jVrbJ8rM5dPeo2k0CiyzvZ9dsBYNa9GwFg1r0bAWDWvRsBYNa9GY67XwGoLKjcBtwLYTtm0NXNltdyRJkqRuGAiArM6bOofqFJ9xy4Czu+2RJEmS1A0DQeN4YK+I2Hi0IiJ2A7YBTuitV5IkSdIMMhA0jgUuBA5vrTsCWJGZl/bTJUmSJGlmGQhqmXkXsA+wfUScGBEnUV0p/uZ+eyZJkiTNHKcdlSRJkgrmEQJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgJJkiSpYAYCSZIkqWAGAkmSJKlgBgKpUBGxRd99kDQ3OF5Iw2YgGJCI2C4ilvXdj7kiIt7bdx969qGIuE/fnehCROw4Yd2zIuKv+ujPbBERCyLi8Ii4f0Tcrx5D7hsRm0fEor77N5s4XpQzXmyIob8vHDsnG+LYGZnZdx80TSLi68CewLWTNtePefXP+cAC4Dpg9yzsjRARzwU+l5nz++7LTIqIp2fmVyas3wq4GnhxZn62+551JyKeDHwWeGJmXtJa/xngacCfZOZ5ffWvTxHxDOAzwM3AIqoxYaP6eQB3ATcBVwHnAP+Smef309v+OF6UM15siKG/Lxw7pzbEsdNAMCAR8VjgxcAH19UUOL5uC3B5Zq6eyb51LSIekZk/XMv2zYCfZOa2HXarUxHxTOCLVIPWmzLzqta21wOvoRrMLgNupwqL86gGtIXAKzLz+q77Pd0i4g+Bk4GvZeaLWusfBOwGPAz4fPsDryQRcURmHjlh/UJgU2ArYBfgIOCZwFMy86xuezmzHC8cLyYp/X3h2Ll2Qxs7F/TdAU2rXwE3ZOZP19UwIlauT7u5KCIeAZwVERdSfXBB8+G1sH48Fbi4nx52IzNPiYjzqL6lOD8i3pWZ760P+78BeDVwFHDK2K6H1es3B+b8B3xmfisifgCcFhEvBc4C/gy4EPhFZp7cawf7N/Fbocy8E7ixflxaH4FcCTyFqoaD4HhRcbxYk+8Lx871MKix00CgwYiIZfU3FRcA/wO8iepoyPuB14+aAe8DVvXSye79OjNfFRH/DLwvIs4ALgVOrn8BeGNmHtveISJePr5uADIzj42IQ4DvUX3T+W7gwxHxm3Xsey1waGb+10x3cqZFxAMz87J7ufs84PTMfOd09qkvjhcTFT9e+L64B8dOyhg7DQQahIj4O+CQiHhcZl4bETdk5jfrbTePnreWb4mI3vrbtcy8AnhBRBwDHEJ1GBMmf8Mx5PMIdwe+CrwS2I7qA+u/19L+vsC3gVcAc/pDLSIeCpxTf+PZtl1EPA34DdW3w1dTfQP43cz8Uavd7wEf7aSzM8zxYu1KHS98X6yVY+fAx04DwbAsBw6KiCetR9tHRsQ3qE4zet4ALio+BdgW+EpEvJA1P6Tm+t9tg9QzHPw78LetdfOBt1DV4lDg4xHx1H562IslUX1y35yZrwOoP8ivysyfrWW/n0XE9zJzKDNqvAK4E1gN3E31ftif6tzxzYAtgZ2A5wDviYjLgDdm5unAlfVjCBwvao4Xa/B9cU+OnZXBj50GgmG5hurCr7uo3qyjN+0iqgQbrcc8qpmGFgJLgF/30N9pk5kXAK+LiK2BVwEP6LlLfdod2Bn4CfCbiHgt1ewHn8/MiwAi4ibgSOD+EfHmsf0fUK/7XGb+b4f9nkmL6tB7xNj6KS8GjIjFmXk78LkZ7VlH6n/7i8bX19+G3mPmmPoXxacDR0XExcBBmXnXzPd05jlerMHxoub7YiLHzkLGTgPBgGTmN1rnPwLVNHLASzJz/9a6oDrstxXw75k5p8NAWz3LxZER8aSI2Jsq/GwVEfu0mo2Wl9ZtRuFoEdWhvqvu8cJzSD0N3OPqGTCeDxxAFQi/2GrzuXqmiPOoDme2p6T9MtUvCH8IzOkP+JZDJ6y7A1jjG66I+IvM/Ei9+FzgU5n5LzPduZ7tGBEL6wvhfiszVwGnRMRVVEcfT4iIA8bbzWWOF44Xk/i+WINj59QGNXY67eiARMR7gEdl5p+01n0OWJqZT2mtOw7YD/gYcGRmXtN5Z2dYfTHcknrxIcCPW5tHyw+humBuNHPERsAnM/PtHXa1ExGxK/Ba4EeZeUxr/WGZeVR/PZt5EfEa4L3ALyZtpjqK9kqqQ76fzXpO8Yh4VWZ+qLOOdiQitszMm1rLe2fml9fS/k+BH1B9k/yMzHz9VG3nKseLNZU8XrSV/r5w7FzT0MdOjxAMy8VUabRtf6oLgQCIiL8EHgw8fGhzB0fEPKqp8c6nmhnhMfX6MzLzya1238jMp4yvH5qIeGRm/jdAZl4MHBoRD46IR2fmf0U1rd6nI+LxmfndiFiemef225vUc78AAB2SSURBVOsZ8RGqe268mHveg2O0fB7VtHA/ae23eUTMy8y7O+zrjIqIhwPfiIj/BG5trd9/6r3YDDipnmnkfhGxT2b+x0z3daY5XqzJ8aLi+2INjp21EsZOA8GAZObHI+LAsXV3RkQCRMSDqZLqE+fC+Wz3wseAP6U617WtuMNgEbEN8J2IuJbq7z+P5k6Kj46IJ1JNB/fiqO5CCvDUiPjh0N4bmbkqWvfdiLF7cNTLv6qfX93a9WdUAfucTjs8sy4Dfgl8aWz9aC75qZYfDlB/sL0FmLUfahvA8aLmeLEG3xc1x841DH7sNBAMzxMj4pdj6xbXqXYxcPgAB3Ai4vnAdcCDMnNlRPxZe3NP3epNVlPmvZtq7uyRoJpF40rgCuDxddvRt3w/prqb4kkddrUrO0Z1sWQAO9TPR3aYYtsDqabXG8yHWmb+OiKuyXXMJT9h+eOtb/yOiYgdM3PWz5oxFceLNTleVHxfTOTYSRljp4FgjouItwE/BT6TmXdQna92ULsJ1ZRyRwCPAN4YER8E3pzDusvgdzPz861lp4uD3357MxIRuwD/Vi8+OCKWtTZvQfV+GcwHfMsCmr/fQqpzXkfay6tbz28G/ojqHNqhG/8/Mr58BVUtzqzPob2Juc3x4p4cL3xfTOLYuXaDGTsNBHPfplTTo70/Ij4PkJlr3DwjIn6dmWcAZwAfiIidgX+KiGcDf56Zq7vu9HTLzN8eroyI+wF/EBGrm1Wxxt8xIv6aMgf467nnIc+290bEdu16DsTlmfk2gIh4Umb+9nSA9nJE7DG27fyhnQt7L/2Qan7tM3vux7RwvFhvRY0Xvi8mcuz83cyZsdNAMMdl5huguvodeBpw34j4HtUNMb5bN1s8ts//AvtFxEuAY4A/77DLXbgNeBTV/RjupLkvw0Kq9/wC4BZg37462JGtI+KAsXXzgHMz8+cR8SKqW9G3XUA1a8Q7uuhghzaKiB2pvuVqPx9tW5TVVHHzxvb7JdWpEt/urqszJyIWA7tEdVPCtkeOrRtf3gzYNiLekDm4qekcLyqOF2vyfVFx7KSMsdNpRweovujrr4DrMvPDEXFVZm4/RdvHActz+PMF30NUU8rtNdBrKuZTzQCxgOpQ7jyq+bEXAp+imkHj88AqqhvYjW5it2nddpchHDkCqC+0fx9VHVZT/T1HN+gbzRv+jsx8X0ScAzwpM2+r9/0ocEdmvnbii88xEbED8BiqeeZHd9xcn2/wAjiB6sLSQdxsaEM5XpQxXmyogb8vHDtrJYydHiEYoMy8AXh7RGxer5pyPuTMPCsilkTEfeprEEryY6qjJ4O5MdtI/eG8tunQAH5/fEVU84//K7A9c+BW6+sjM4+n+mVnfbxt9IFW+xmwz1AOfWfmz4Gf35t9I+IHrOXupAVwvBgzxPHiXhjy+8Kxs1bC2OkRAkmaQkRsmgO6k/fvIiIWZ+btffdD0uzn2NmYK2Pn+DlfGpD6oqipto3PsSxpjB9ojbnwgSZpdnDsbMyVsdNAMFAR8SDgW1Nsuw/wurH5hIsWETtHxP/pux/TKSKe0HcfZouIWBQRx667ZRkiYmE9/fBoeaM++zPXOF6oFI6daxry2Ok1BAMSa95Kfm/gAVM0fSnVle+DuwhqknWdw1jP0HQWcOFUbeaaiHgx1fzhi9fVthBvBg4EXtZ3R2aJP6WaeOC1EfFMqhvmnLge+90JfCUzx2faGAzHC41ExP2Bl1PNxjd+Y7KNgLsz8xdd96tjjp1rGuzY6RGCgagH9P83Wq5nDTpvQrvtqW6r/cXMHNQ3XJNExGbAaWtrU98s5E3d9KgzW1LNADGliFgeEVt01J++HQVc1HcnZoOIeAPVvUtG0xJfSHVB5A+o5sz+0/rn+PMfAvcHToyIhR13uxOOF1MrbLwY+TvgrcA1Ex6XA/891P8LLY6dtaGPnQaC4ZjPPY/4rHEOX0QsAD5B9eY8sJtu9e4YqvszrFVm/t8O+tKZOhB+Z6rtEfFp4PtUU8oNXj0l4HV996NvEfEQ4A+B11MfIazvS3JNZh6XmccC12bmsePP6+VvAS/KzDv7+jvMMMeLCUobL1peBXwrM+dn5rz2A/jPzPy9Af9fABw7R0oYOz1laCAy87iIOGiq7fV5bl8E7gCeVdAUo68FSj03duIpYRGxP/Ai4FjgLzrtUb8iIv5pA/dJ4DLg3wcyz/qvMvN5ABFrnAGR6/Ec4OL6rudD5XgxpuDxgsy8e/zuxO3NnXamX46dBYydBoJhmThA1cl2BfD5zPzXbrvUr8y8ISIu67sfs8wbgBMzc8oAOWA7bmD7jYC/BR5J9W3hnBURmwCfbt1Fc6eI+Eeqc6PX9XxkdUR8ezZ/y/W7cLyYqOTxQg3HzoGPnQaCOW4d89tGRBwMLAVekpmlHvYr6ZuctapvJLQU+OO++9KDzMyXbOhOEXENwzhkvjPwVao7bd5NdbfNX9XbVgM3U32QjT//1djr3I/q/OmhcryoFT5eqOHYWcDYaSCYwyJiY+A/I+LketV4In0AVapfDRxaH+Ya3XJ8Hs2tx1dk5hWddbx747NDlOwFwCFzZV7kvkXEIuCMzHxr3335XWXm+cD5o+WIeFZmrqifPyczPzjF8xW9dLg/jhcNxwvdK46dc2/sNBDMbU8ArgceTTWl1RLgYa3tWwJ/D3wTuJHqg270mF8/FgL7Ul1MN6dFxGMy85wJm0r9xi8iYkfW/AVnKfDTejq9qcwH7gNcVtC1JlPZFHhP352YIdk6wri+58EOhuPFPRQ/XtQTbxxHa8Y+YNuIeOmE5uPrR5+rC4BbM/NTM9fTOcGxc44xEMxhmfk14Guj5Yg4IzNf2Fr+BrA18CDgLZn5ve572Y36g+zMiDh7wuZHts79K83PJqx73Xrsl8BfAx+Y3u706jcRsQRYlJk3AkTEksy8daodMvMG4IauOtix0XmutwEPjYjj6nWTnrddlZmHddzXaeV4MaXSx4unA3sAD6U6sp7ADsBrJrTdgeoidKj+r8yrfy4A5kXEOZl56Yz3uBuOnWsa5NhpIBiW8UR6M9UUen8D/L+IeENm/nv33erEtsDbgVX1o12Lz6/nazx/ujs1C2y6ge3nUY0LixjejeteDDwceBvw1HrdIRHxgcycc9/mTINjgZ8CD6H6xeZOqgsBT6T6QFsIfIbmqOJv3xvruHZpLnC8mKzo8SIzT2PsPhT1F21PHm871fqBcuxc0yDHTgPBwNVzCL8rIr4MnBQRkZkf77tf060+9D/p8P96i4ihfcBnZt7Wdydmi8y8sb6OZrPW6m8CBwGD+z+xNhHxPOC+mbmK6tzY8yNia+CY0VHGiHjFEMcKcLyYguPFZFP9wlvML8KOnY0hj53emGxYFkfExH/TzPwBsCdwcEQ8u9tuSf2JiKdExLz6/8bZwG1RmUd1h8lnRMTiUZvxR7+9nzGbAIsBImLLiNgBuAVo/0K4Qx8dkzQ7OHZONNixc6j/YKVaAGwz1cbMvBbYB3hDRDygs15JPYmIpcApVId076Q6PeSPqE5vGK17DnBra3mNR0TcEBEv6L730ysiHhIRn4iI7YGTW5teDfwY+B/g2RFxRURcAbwxIn5eL18ZEVdFxHVTnHcvDdVUs04NejYqx85GKWOnpwwNy5sy8+rW8n3GG2TmzRGxH9XV/xs8r7A0x9wB7E41f/ToIsEvAO2jZFtQzSryhLpN21bAfwGHA5+b6c7OsAdTTUV8KfB94OqI2AL4MPBRqg/xg4EP1e2XUJ1W8xhgJdUXSAuBhfWph8WcMqGilXrKkGNno4ix00AwIJn5zbFVvxcRm2bmr8faXRMRH4qI52bmSR12cbYb3P+Hdc0EMXSZuRJY486zEbGqngFj5IaI+DGw74SL7m+IiGuBp8xwV2dcZp4CnBLVXTefAxxB9e3W2cAnqb75uqN1HvltEfEV4MDMPLqPPs9yjhcDFxEPApZHxPcnbF4W1T2Anj1bf8H7XTh2NkoZOz1laNgOHw8DI/UUpIs67s9st6G3Zp/tgupbDa3pHkfOqL75+ueI2K69MiJ2Bt6TmTd10rMO1B9apwLfoXrP/19gf+AXVNcYbd9qfhxwWERs2XlHZz/Hi+HbFDgE+CeqWamOpJpp5+3AS6l+Gdyit951z7FzwGPn4L7hUCMzv7KO7Z/pqi9zxAV9d2CavSMzL+y7E7PQmRPWfYXqfh3Xjq2/LDM/OuM96l4CN9UzZXwW+Gx9zvA7WPNUiG8Dl1Ad/h/MB/s0cbwYuHoyjh/03Y9Z5MwJ6xw7BzJ2xgCPdEmSpslsPudVkmaruTZ2GggkSZKkgnkNgSRJklQwryHQoNQ3QzkYOH4Dd12dmb+ZgS71xlo0rEXDWjSsRcNaNKxFw1o0hl4LTxnSoETEkcA/cO/miL4SeFFmTppibs6xFg1r0bAWDWvRsBYNa9GwFo2h18JAoEGJiM2oZj3YbwN33RH4JvD9zHzctHesB9aiYS0a1qJhLRrWomEtGtaiMfRaeMqQBiUzb4mI2zPzZxuyX0T8guouhHvPTM+6Zy0a1qJhLRrWomEtGtaiYS0aQ6+FFxVLlW2Ad2fmzX13ZBawFg1r0bAWDWvRsBYNa9GwFo05UQsDgVRZSXXHRVmLNmvRsBYNa9GwFg1r0bAWjTlRC08Z0hAt3NAdhnR79THWomEtGtaiYS0a1qJhLRrWojHYWniEQEN0/747MItYi4a1aFiLhrVoWIuGtWhYi8Zga2Eg0BCd3ncHZhFr0bAWDWvRsBYNa9GwFg1r0RhsLZx2VJIkSSqYRwg0KBFxn4h4RkRs13df+mYtGtaiYS0a1qJhLRrWomEtGkOvhYFAQ/Ml4GTgmL47MgtYi4a1aFiLhrVoWIuGtWhYi8aga+EsQxqMiHgBEMDumXlR3/3pk7VoWIuGtWhYi4a1aFiLhrVolFALA4GG5PrMfNpoISLeCnxjPfcNqunErsjMn8xA37pmLRrWomEtGtaiYS0a1qJhLRqDr4UXFWuQImJv4CTgrvqRwN31T+qf0XrMowrI52bmH3fe4RlkLRrWomEtGtaiYS0a1qJhLRpDrYWBQJIkSSqYFxVLkiRJBTMQSJIkSQXzomIVIyKeBdxcLz4YuCUzT+yxS72xFg1r0bAWklQmjxCoJN8BtgD2Bj4E3AcgIp4QEZ+LiL/qs3MdsxYNa9GwFrWIeFZE/FH9ODgiXtR3n/piLRrWomEtGkOohYFAgxQRDxxfl5k3AGcD9wd+BHw6IvYETgVWAld12smOWIuGtWhYi3UyHDWsRcNaNKxFY87XwlOGNDgR8RfAOyLibOBqql9kNgMeCuwE/BtwCLAR8FLgEZl5RT+9nVnWomEtGtZiTRHxwMy8rL0uM2+o6/Nn3DMcncJAw5G1aFiLhrVoDLUWTjuqwYmIBcAZwD8CmwNLgFXAz4HzMvOOHrvXKWvRsBYNa9EYhSOqIyNThaN3AvOBfwaOGmo4shYNa9GwFo0h18JAoEGKiJMz81lj6zYC3gfsBuyXmde0tm0K3JoD/A9hLRrWomEtKoajhrVoWIuGtWgMuRaeMqRBiIjfB1ZQ/Ue9A3hARBwE3ARcCVwCfBLYDnj12C86hwNHAGcCT2OOsxYNa9GwFpNl5l0RcVNmntFePwpHEVFMOLIWDWvRsBaNIdfCQKCheARwLdVUiaupDuE9DdiR6gLJbYAbgT0y89rRThFxKPBA4JnANzvu80yxFg1r0bAWNcNRw1o0rEXDWjRKqYWnDGmQIuJE4ODMvCUillKdBnEBcCDVf9hv1+02y8xbeuzqjLMWDWvRKLkWEfECYF/gLqpw9HTge6xfOFoOfBb45lw+PWDEWjSsRcNaNIqpRWb68DG4B/A3wBb186cCG9fPtwQ+Aezddx+thbWwFrPjAZwIbFY/X1r//d8E/AB4YqvdZn331VpYC2thLWbi4X0INDgR8QTgjZk5uuPqLpm5EiAzb8rMlwPLI+JBdfsnRcT3I+L/66fHM8daNKxFw1rcwzk09+V5FPBXmfle4MnAwRGxN0AO7EjJFKxFw1o0rEVjkLUwEGiIfkx11f/IfSNi43aDzHwHsGVEPIdqirBvMpDzo8dYi4a1aFiLmuGoYS0a1qJhLRpDroUXFWsQIuLZVBdN/rxetTIiXlE/vy+wIiLOqpcTuCIzvx4R/5OZX+y4uzPKWjSsRcNaTGliOBp9yEMVjiLi0XU4+huqYHR2x/3sgrVoWIuGtWgMthYGAg3FLsCy+ufdVLcQ/8PW9mcAC6l+0ZkHPCsijsnMt3Td0Q5Yi4a1aFiLmuGoYS0a1qJhLRql1MJAoEHIzKPbyxFxRmYe1Fr+CPClzPyPevlk4PyI2A64KzOv67TDM8haNKxFw1qswXDUsBYNa9GwFo0yajETVyr78NH3g2q+4O1by88EvtVafn398+nAl4FbgY9ST8U7pIe1sBbWYt21GFv+CLBPa/lkYH+qecbv23d/rYW1sBbWYrofXlSsoboemN9a/gbwBxFxYL28AiAzv5KZewPPBZ5NlfyHxlo0rEXDWrRExPatxVOBv2stfyMzTwAeDhwXEbdGxEcjIjrtZEesRcNaNKxFY5C16DuR+PAxEw9g0YR1b2UtaR3YqO9+WwtrYS16qcVngR1by5tQXTh4YL0cY+33orrr85Z9991aWAtrYS2m4+GdiiVJRYuIRZm5amzdW4EP5RTXTkTERpn5my761yVr0bAWDWvRGGotDASSJK1DRMzPzNV992M2sBYNa9GwFo25WAuvIZAkFS8iHjm2PK/1fHsGeFO2qViLhrVoWIvGEGthIJAkFS0i3gW8t7W8J/CJVpMHA4/uuFu9sBYNa9GwFo2h1sJAIEkq3UlAewaQ7YEdRguZeSZwFmWwFg1r0bAWjUHWwkAgSSpaZn5/bPkLk5p11J1eWYuGtWhYi8ZQa2EgkCRp3Wb3HOLdshYNa9GwFo05VwsDgSSpOBExf92t1jDnvvFbX9aiYS0a1qJRQi0W9N0BSZJ6cGxE3A3cVS/vGhEfb22ftPwxqi/S5gOLgBOnOF1grrEWDWvRsBaNwdfC+xBIkooSEQuAI4DRB/zdVN/otR+jQ/4x9phfPxYAP8/M/9Np56eZtWhYi4a1aJRSCwOBJEmSVDCvIZAkFedenBM8WNaiYS0a1qJRQi08QiBJKk59c6HfB26Zqknr5zyaUwBG5wTPB/4zMz84w12dcdaiYS0a1qJRQi28qFiSVKLbgIuAVVTnBR8CfLS1/c8nLP8b1Qf8PKqLBLfopKczz1o0rEXDWjQGXwuPEEiSihcRZ2Tmk9d3ecisRcNaNKxFY4i18BoCSZLuOW/4upaHzFo0rEXDWjQGVwsDgSRJ97RJ3x2YRaxFw1o0rEVjztfCQCBJEmw1tvyA8QYRsaijvvTNWjSsRcNaNAZXCwOBJEmwZGz5dWPLwYQP/YGyFg1r0bAWjcHVwkAgSRL8UXshMz8ztv1U4OruutMra9GwFg1r0RhcLZxlSJIkSSqYRwgkSZKkghkIJEmSpIIZCCRJkqSCGQgkSZKkghkIJEmSpIIZCCSpQBHxpoh47oT1L4yIB/fRpw0VEY+PiHlj6+53L15nmw1svzAi9tjQP0eSZqsFfXdAktSL5VQ31zlpbP2+wCsjYp/MvHtdLxIRTwa2zszPzkAf1/bnzgdOA74aEftlM4f2H0XEwzLzLRvwcp+OiMXAHevZfkvgIRGxLDMv34A/R5JmJY8QSFKZ7gJ+PsX6M9YnDNTOBP48Ir4aERuvrWFEbBYRb4uI6fgy6jHA5sA/5po31Pk08IKI+PsNeK07gQ9n5pMy80nAJcCZreXjgctby4cD1xgGJA2FgUCSynQ3QETcNyKe2Fq/mvqb8vrUmL+MiJjqRepfxl8P7AU8td7v4xFxZUR8JyLOHD2ArwL/ABw8Df3fG/h6Zv54Qn9OBJ6zAa/lHTolFc1ThiSpABGxEfBJYOt61TJgT+AfgY0i4n3Ao6m+eX98ROwFbAHsCnwN+OmE19wnM/8jMy+MiFOAcwEy8xVT9GEn4DKqb9yn6ufGwMaZef1a2gTwEuCNUzQ5Dvj62D6HA9/4/9u7/9C/qjqO48/3dzVWmav9qFWrJSr9IFCygmjFkrSIIokioT/6R6HIyECLpB+LTDNSg2gJWazVTLSwaZChWMNytegXlEppsX5sbkJzNhsr89Uf537ls/v97Xdz++4+H/Dhwz333HPP/f7z/bzvOed9kmybpP4T+V+46AlcI0nHpDp0pFWSdLyqqjW0EYCdwDeAnya5tju3jDZqcA1wW5KvV9WZwEVJ3jpFeweBK5J8apb3fzEtIHhmkv1T1FkHrEuyfpp23gh8EziJtubhku65/jvFJYuBVwK7gdclOWSqVFX9DFgOPNC7bg2wY5L2lgOrkqycqo+StJA4QiBJA5Hk8R+3o7OAujfue5Okql4I7O1OLQV2TdPko8AdR6CrM3k/LXh5BfAD4G5gR5IJAUFVnQAcSPK/adq7ALg3yYHetQ8AW5Jc3St/E3Dy/B5Bko4dBgSSNFynVdWngQeB+6rqV8CLgL91508A/j3N9Y8e4f5NUFWnAGuB59MW9j5G6/tqJl8kfRbwuao6L8ldk7R3CfBBYGdVPTJyagx4LvDOqnrHJO0+VlW/SbJ9no8kSUedAYEkDUT3tvxM4G3dZwtwZZL9VfUMYAOwipZlB+A/wInTNHk05px+FLgIuC7J7pHy86vq8iT91KEvoQUPE9ZAACS5DLisqk7uju8HqKqXA5uTvH68bre+4WPAVUn2Ha4HkqSjzYBAkgagqj5Dm2u/HbgcWAJsG5/Ln+SRqvo98E9gc1W9h/bG/WXd9Sto8++3jDQ729Sk0/XrBcBXRopWACt6G399NcmPqupU4OnAd4Hrek39FrgY+Gyv/DRgYy94mMzptOf++UjZvi470rjFwGu7e/X3b5CkBcuAQJKGYQNwf5JNAFX1rtGTVfVsWuae02kjB1fRsvicVFXPA14D9N+Kz3uEIMk/GEkROsOi4g/Q5vtPlgb1dmBjVV2T5MGR8jNozzWTg7QpSOumqlBVq4BdSQwGJB1XDAgkaQC6N+SbRorGOPQH/ZeADyXZVVUXAF9McqCqrgWuBP4K3Pqkdbinqk4Evpbkoapa3D+f5F9VdR9tPcD67prlwNNooyKzsao3ItA34b6SdDwwIJCkgaiqMeDDtHUEbwC+1ZV/ErghyVaAJNur6tzuskuBrcC7gT/TdiYe96StIUjyMPBwd1jQsiP1din+NW1txPrueC1wU6/OdGY1QjCHbkvSgmBAIEkD0WXkubqq9gB/AG6vqlcD1yf5U6/uzi4d6SLaD+tz6XYwHjHlDsZHWI18j/7Yv4e2L8G4tcCNc2jXEQJJg2RAIEkDUlVvAX6SZHO3bmB1kl9255YC702yAaDbl+AKYFOSjZM1dwS6eDcw5S7FvfuOcejC5r8A148cv5SWlWi2HCGQNEgGBJI0LBcC7wNIsreqLq6qfUnuSLKvqs6oqk8kubSr/3ngd1X19iR39to67AFBkj3AnhmqjU1x/5uB7wNU1XOAP85huhA4QiBpoAwIJGkgquos2tqB0Sw8dwFfAF7VHd8I3FJVX06yL8mOqroF+AjQDwjGmCEoqKpltFShu4HVXfF0uwbPxnhAsAh4fHfi3m7EZwM3jPRjJfBt4MIk90zR7pxGCLrRlh8nOTjXB5CkY4kBgSQNQFUtATYD3+nWEoz7BS0Tz7it3Wf/SNlNtM29+p4CPHWGWwd4M23qzqnA35McmFvvJ1jUfS+pqluBNbQ9EyYEGm0ZxCE+XlXnAc+iZV1a0pUvZ5YjBF2dpbQUrbdV1TlJptvRWZKOaTW30VRJ0kLVpeF8qPcmfT7t3Qmcn+TeWdRdBvyQ9oZ+2zzvuxL4HnD2JDsTz6WdU2j7D+w8XH8TSVqIDAgkSQvKJOlGJUnzYEAgSZIkDdjYzFUkSZIkHa8MCCRJkqQBMyCQJEmSBsyAQJIkSRowAwJJkiRpwAwIJEmSpAEzIJAkSZIGzIBAkiRJGjADAkmSJGnADAgkSZKkATMgkCRJkgbMgECSJEkaMAMCSZIkacD+D1InVDXk211fAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 302,
       "width": 386
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ht.groupby('热门+位置').totalCount.mean().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以明显看出，非热门英雄的人气值比热门英雄的人气值高，这可能是因为热门英雄供过于求，人数过多导致的拉低了人气平均水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 直播推荐标签  \n",
    "[虎牙直播主机游戏品类推荐与标签申请规则总览](http://blog.huya.com/policy/537)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "ht['标签'] = ht['attribute'].apply(lambda x: re.findall(\"1': {'sContent': '(.*?)'\", x))  # 提取ListPos1的sContent标签，即标签，格式['上电视']\n",
    "ht['标签'] = ht.标签.apply(lambda x: x[0] if len(x)==1 else np.nan)     # 去掉列表的括号[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# 用出现最多次的标签作为当次主播开播的标签\n",
    "# 提取{用户id：标签}思路：分别对每个用户id进行标签的value_counts，并且按降序排序，然后把作为index的用户id转为columns，方便对用户id去重，保留第一列，即保留了出现次数最大的标签。最后变为dict\n",
    "tag_dict = ht.groupby('用户id').标签.value_counts(sort=True).rename('出现次数').reset_index().drop_duplicates('用户id').set_index('用户id').标签.to_dict()\n",
    "pht['标签'] = pht.用户id.map(tag_dict)\n",
    "pht.标签.fillna('无', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "上电视     5677\n",
       "大神推荐    2794\n",
       "魅力新星     327\n",
       "超粉之星     309\n",
       "无        280\n",
       "Name: 标签, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pht.标签.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 直播标题的LDA主题提取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('data\\用户id_直播标题字典.txt', 'r') as f:\n",
    "    title_id_dict = eval(f.read())\n",
    "# 段位较低（白银），以娱乐为主（快乐，克隆模式），新人直播标题（欢迎来到××的直播间，我是一颗小虎牙）—— 低段娱乐\n",
    "# 段位较高（王者、艾欧尼亚、教学、），一起玩（黑色玫瑰、上车、车位、大乱斗）—— 高段开黑"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['直播标题主题'] = pht.用户id.map(title_id_dict).map({'1':'低段娱乐', '2':'高段开黑'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "低段娱乐    4722\n",
       "高段开黑    4665\n",
       "Name: 直播标题主题, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pht['直播标题主题'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 公告LDA主题提取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('data\\用户id_公告字典.txt', 'r') as f:\n",
    "    ann_id_dict = eval(f.read())\n",
    "# 主题1：大神直播\n",
    "# 主题2：欢迎来到××的直播间，没有什么信息含量\n",
    "# 主题3：新人求订阅\n",
    "# 主题4：直播时段、打赏机制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "公告_主题号_主题名_字典 = {'1':'能力描述', '2':'缺少信息', '3':'新人求订阅','4':'时段&粉丝机制'}\n",
    "pht['公告主题'] = pht.用户id.map(ann_id_dict).map(公告_主题号_主题名_字典)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "缺少信息       4704\n",
       "时段&粉丝机制    2079\n",
       "新人求订阅      1396\n",
       "能力描述       1208\n",
       "Name: 公告主题, dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pht.公告主题.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 直播时长"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上半天直播时长"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\software\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:10: FutureWarning: Passing integers to fillna is deprecated, will raise a TypeError in a future version.  To retain the old behavior, pass pd.Timedelta(seconds=n) instead.\n",
      "  # Remove the CWD from sys.path while we load stuff.\n"
     ]
    }
   ],
   "source": [
    "# 上半天天直播开始时间\n",
    "a = ht[ht.get_time<'2021-04-04 12:40:00'].groupby('用户id').get_time.min().rename('上半天直播开始时间')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "\n",
    "# 上半天天直播结束时间\n",
    "a = ht[ht.get_time<'2021-04-04 12:40:00'].groupby('用户id').get_time.max().rename('上半天直播结束时间')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "\n",
    "# 上半天直播时长\n",
    "pht['上半天直播时长'] = (pht['上半天直播结束时间'] - pht['上半天直播开始时间']).fillna(0)\n",
    "pht['上半天直播时长'] = pht.上半天直播时长.apply(lambda x: x.total_seconds()/(60*60))  # 转为小时"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下半天直播时长"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\software\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:10: FutureWarning: Passing integers to fillna is deprecated, will raise a TypeError in a future version.  To retain the old behavior, pass pd.Timedelta(seconds=n) instead.\n",
      "  # Remove the CWD from sys.path while we load stuff.\n"
     ]
    }
   ],
   "source": [
    "# 下半天天直播开始时间\n",
    "a = ht[ht.get_time>='2021-04-04 12:40:00'].groupby('用户id').get_time.min().rename('下半天直播开始时间')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "\n",
    "# 下半天天直播结束时间\n",
    "a = ht[ht.get_time>='2021-04-04 12:40:00'].groupby('用户id').get_time.max().rename('下半天直播结束时间')\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')\n",
    "\n",
    "# 下半天直播时长\n",
    "pht['下半天直播时长'] = (pht['下半天直播结束时间'] - pht['下半天直播开始时间']).fillna(0)\n",
    "pht['下半天直播时长'] = pht.下半天直播时长.apply(lambda x: x.total_seconds()/(60*60))  # 转为小时"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['直播时长'] = pht.上半天直播时长 + pht.下半天直播时长\n",
    "pht.drop(columns=['上半天直播时长','下半天直播时长'], inplace=True)            # 删除掉计算的中间字段"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "因为数据爬取是间隔性的，无法准确测量直播时长，所以为了降低异常值的影响，增加模型的稳定性，对`直播时长`采用分箱处理。  \n",
    "2小时以下（50%以下），2-6（50-75%），6小时以上（75%以上）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9387.000000\n",
       "mean        3.892445\n",
       "std         4.778028\n",
       "min         0.000000\n",
       "25%         0.015556\n",
       "50%         2.023333\n",
       "75%         6.010278\n",
       "max        23.295556\n",
       "Name: 直播时长, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pht['直播时长'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['直播时长_分箱'] = pd.cut(pht.直播时长, bins=[-1,2,6,25]) # , labels=['<2','2-6','6-10','>10']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 在播时段：  \n",
    "  \n",
    "    14:00 - 01:00 黄金时段  大于均值  \n",
    "    01:00 - 14:00 非黄金时段  小于均值  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_hour(t):\n",
    "    return t.hour if t else np.nan\n",
    "pht['上半天直播开始时间点'] = pht.上半天直播开始时间.map(get_hour).fillna(-1)  # -1填充，方便下一步的运算\n",
    "pht['下半天直播开始时间点'] = pht.下半天直播开始时间.map(get_hour).fillna(-1)\n",
    "\n",
    "pht['开始直播时间点'] = pht[['上半天直播开始时间点','下半天直播开始时间点']].apply(lambda x: x[0] if x[0]>x[1] else x[1], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['活跃时间'] = pd.cut(pht.开始直播时间点, bins=[0, 1, 14, 25], labels=['黄金时段_2', '非黄金时段',  '黄金时段'], right=False).apply(lambda x: x[:4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 蓝光  \n",
    "    是否有蓝光\n",
    "    蓝光清晰度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 是否有蓝光"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = ht.drop_duplicates('用户id')[['用户id','isBluRay']].rename(columns={'isBluRay':'是否蓝光'})\n",
    "pht = pd.merge(pht, a, on='用户id', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 蓝光清晰度\n",
    "    4M以下：中清晰度  80%\n",
    "    4M以上：高清晰度  20%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "blueRay_dict = ht.groupby('用户id')['用户id','bluRayMBitRate'].head(1).set_index('用户id').bluRayMBitRate.apply(lambda x: x[:-1]).to_dict()\n",
    "pht['蓝光清晰度'] = pht.用户id.map(blueRay_dict).astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['蓝光清晰度'] = pd.cut(pht.蓝光清晰度, bins=[0,4,100], labels=['4M以下', '4M以上'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 个人信息表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\software\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3058: DtypeWarning: Columns (36,37) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "pi = pd.read_csv('data\\个人信息.csv')   # personal_infomation 个人信息表"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "个人信息表pi:\n",
    "- 用户id\n",
    "- 标签\n",
    "- 上次开播时间\n",
    "- 省份\n",
    "- 城市\n",
    "- sex: 性别\n",
    "- fans: 订阅量\n",
    "- 个人等级——观看直播获得的等级\n",
    "- 主播等级——开播获得的等级"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 地区"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "省份所在区域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "province_dict = pi.set_index('用户id').省份.to_dict()\n",
    "pht['省份'] = pht.用户id.map(province_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# 省份映射到区域   \n",
    "with open('data\\省份所在区域字典.txt', 'r', encoding='utf-8') as f:\n",
    "    proDic = eval(f.read())\n",
    "\n",
    "pht['区域'] = pht.省份.map(proDic)  # '华东', '未知', '华北', '西南', '华中', '华南', '东北', '西北', '海外'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "城市：前线城市、非前线城市"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "province_dict = pi.set_index('用户id').城市.to_dict()\n",
    "pht['城市'] = pht.用户id.map(province_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "qxCity = ['北京','上海','广州','深圳','成都','重庆','杭州','武汉','西安','郑州','青岛','长沙','天津','苏州','南京','东莞','沈阳','合肥','佛山','昆明','福州','无锡','厦门','哈尔滨','长春','南昌','济南','宁波','大连','贵阳','温州','石家庄','泉州','南宁','金华','常州','珠海','惠州','嘉兴','南通','中山','保定','兰州','台州','徐州','太原','绍兴','烟台','廊坊']\n",
    "pht.loc[pht.城市.isin(qxCity), '是否为前线城市'] = 1\n",
    "pht.loc[~pht.城市.isin(qxCity), '是否为前线城市'] = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 性别、订阅量、个人等级、主播等级"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 性别有6000+条缺失值，用朴素贝叶斯进行填充。\n",
    "with open('data\\用户id_性别字典.txt', 'r') as f:\n",
    "    sex_dict = eval(f.read())\n",
    "    \n",
    "pht['性别'] = pht.用户id.map(sex_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "personal_data_dict = pi.set_index('用户id')[['fans','个人等级','主播等级']].rename(columns={'fans':'订阅量'}).to_dict()\n",
    "for key, values in personal_data_dict.items():\n",
    "    pht[key] = pht.用户id.map(values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "考虑到字段`订阅量`缺失值过多，且订阅量分布右偏严重，故对`订阅量`字段做分箱处理（按百分比分箱）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      3195.000000\n",
       "mean       3384.297966\n",
       "std       19646.072402\n",
       "min           0.000000\n",
       "25%          13.000000\n",
       "50%          63.000000\n",
       "75%         734.000000\n",
       "max      627714.000000\n",
       "Name: 订阅量, dtype: float64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pht.订阅量.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "15、60、700、缺失"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht['订阅量'] = pd.qcut(pht.订阅量, q=[0,0.25,0.5,0.75,1], labels=['15以下','15-60', '60-700','700以上']).astype(str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 保存数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 删除掉不需要的字段 \n",
    "pht.drop(columns=['上半天直播开始时间', '上半天直播结束时间', '下半天直播开始时间', '下半天直播结束时间', '直播时长','上半天直播开始时间点', '下半天直播开始时间点', '开始直播时间点',\n",
    "                  '是否为钻石公会','公会规模','省份','城市'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>用户id</th>\n",
       "      <th>平均人气</th>\n",
       "      <th>贡献榜总人数</th>\n",
       "      <th>贡献榜总金额</th>\n",
       "      <th>是否有收入</th>\n",
       "      <th>贡献榜平均用户等级</th>\n",
       "      <th>高等级用户数</th>\n",
       "      <th>高等级用户数占比</th>\n",
       "      <th>贵族数</th>\n",
       "      <th>金主数量</th>\n",
       "      <th>贡献榜人均金额</th>\n",
       "      <th>广泛贡献用户数</th>\n",
       "      <th>守护者个数</th>\n",
       "      <th>视频平均时长</th>\n",
       "      <th>视频平均每周更新频率</th>\n",
       "      <th>视频平均点赞数</th>\n",
       "      <th>视频平均评论数</th>\n",
       "      <th>视频平均分享数</th>\n",
       "      <th>视频平均观看次数</th>\n",
       "      <th>公会概况</th>\n",
       "      <th>英雄个数</th>\n",
       "      <th>英雄概况</th>\n",
       "      <th>标签</th>\n",
       "      <th>直播标题主题</th>\n",
       "      <th>公告主题</th>\n",
       "      <th>直播时长_分箱</th>\n",
       "      <th>活跃时间</th>\n",
       "      <th>是否蓝光</th>\n",
       "      <th>蓝光清晰度</th>\n",
       "      <th>区域</th>\n",
       "      <th>是否为前线城市</th>\n",
       "      <th>性别</th>\n",
       "      <th>订阅量</th>\n",
       "      <th>个人等级</th>\n",
       "      <th>主播等级</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2456843900</td>\n",
       "      <td>18115.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.8</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>560.2</td>\n",
       "      <td>无公会</td>\n",
       "      <td>1</td>\n",
       "      <td>热门上单</td>\n",
       "      <td>上电视</td>\n",
       "      <td>高段开黑</td>\n",
       "      <td>缺少信息</td>\n",
       "      <td>(-1, 2]</td>\n",
       "      <td>非黄金时</td>\n",
       "      <td>1</td>\n",
       "      <td>4M以下</td>\n",
       "      <td>西北</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1279528989523</td>\n",
       "      <td>18132.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>无公会</td>\n",
       "      <td>0</td>\n",
       "      <td>未知</td>\n",
       "      <td>上电视</td>\n",
       "      <td>低段娱乐</td>\n",
       "      <td>缺少信息</td>\n",
       "      <td>(-1, 2]</td>\n",
       "      <td>黄金时段</td>\n",
       "      <td>1</td>\n",
       "      <td>4M以下</td>\n",
       "      <td>华南</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>nan</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1579765664</td>\n",
       "      <td>18156.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>白金小规模公会</td>\n",
       "      <td>1</td>\n",
       "      <td>热门上单</td>\n",
       "      <td>超粉之星</td>\n",
       "      <td>高段开黑</td>\n",
       "      <td>缺少信息</td>\n",
       "      <td>(-1, 2]</td>\n",
       "      <td>黄金时段</td>\n",
       "      <td>1</td>\n",
       "      <td>4M以下</td>\n",
       "      <td>华东</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>60-700</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1199549875013</td>\n",
       "      <td>18166.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>无公会</td>\n",
       "      <td>0</td>\n",
       "      <td>未知</td>\n",
       "      <td>大神推荐</td>\n",
       "      <td>高段开黑</td>\n",
       "      <td>新人求订阅</td>\n",
       "      <td>(-1, 2]</td>\n",
       "      <td>黄金时段</td>\n",
       "      <td>1</td>\n",
       "      <td>4M以下</td>\n",
       "      <td>华中</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>60-700</td>\n",
       "      <td>3.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1199536558238</td>\n",
       "      <td>18196.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>无公会</td>\n",
       "      <td>1</td>\n",
       "      <td>热门上单</td>\n",
       "      <td>上电视</td>\n",
       "      <td>低段娱乐</td>\n",
       "      <td>缺少信息</td>\n",
       "      <td>(-1, 2]</td>\n",
       "      <td>黄金时段</td>\n",
       "      <td>0</td>\n",
       "      <td>4M以下</td>\n",
       "      <td>华东</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>nan</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            用户id     平均人气  贡献榜总人数  贡献榜总金额  是否有收入  贡献榜平均用户等级  高等级用户数  高等级用户数占比  \\\n",
       "0     2456843900  18115.0     0.0     0.0      0       -1.0     0.0       0.0   \n",
       "1  1279528989523  18132.0     0.0     0.0      0       -1.0     0.0       0.0   \n",
       "2     1579765664  18156.0     0.0     0.0      0       -1.0     0.0       0.0   \n",
       "3  1199549875013  18166.0     0.0     0.0      0       -1.0     0.0       0.0   \n",
       "4  1199536558238  18196.0     0.0     0.0      0       -1.0     0.0       0.0   \n",
       "\n",
       "   贵族数  金主数量  贡献榜人均金额  广泛贡献用户数  守护者个数  视频平均时长  视频平均每周更新频率  视频平均点赞数  视频平均评论数  \\\n",
       "0  0.0   0.0      0.0      0.0    0.0    30.8    0.416667      0.0      0.0   \n",
       "1  0.0   0.0      0.0      0.0    0.0     0.0    0.000000      0.0      0.0   \n",
       "2  0.0   0.0      0.0      0.0    0.0     0.0    0.000000      0.0      0.0   \n",
       "3  0.0   0.0      0.0      0.0    0.0     0.0    0.000000      0.0      0.0   \n",
       "4  0.0   0.0      0.0      0.0    0.0     0.0    0.000000      0.0      0.0   \n",
       "\n",
       "   视频平均分享数  视频平均观看次数     公会概况  英雄个数  英雄概况    标签 直播标题主题   公告主题  直播时长_分箱  活跃时间  \\\n",
       "0      0.2     560.2      无公会     1  热门上单   上电视   高段开黑   缺少信息  (-1, 2]  非黄金时   \n",
       "1      0.0       0.0      无公会     0    未知   上电视   低段娱乐   缺少信息  (-1, 2]  黄金时段   \n",
       "2      0.0       0.0  白金小规模公会     1  热门上单  超粉之星   高段开黑   缺少信息  (-1, 2]  黄金时段   \n",
       "3      0.0       0.0      无公会     0    未知  大神推荐   高段开黑  新人求订阅  (-1, 2]  黄金时段   \n",
       "4      0.0       0.0      无公会     1  热门上单   上电视   低段娱乐   缺少信息  (-1, 2]  黄金时段   \n",
       "\n",
       "   是否蓝光 蓝光清晰度  区域  是否为前线城市   性别     订阅量  个人等级  主播等级  \n",
       "0     1  4M以下  西北      1.0  1.0     nan   1.0  17.0  \n",
       "1     1  4M以下  华南      0.0  1.0     nan  11.0   4.0  \n",
       "2     1  4M以下  华东      1.0  1.0  60-700   2.0  12.0  \n",
       "3     1  4M以下  华中      1.0  1.0  60-700   3.0  13.0  \n",
       "4     0  4M以下  华东      0.0  2.0     nan   2.0   6.0  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pht.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "pht.to_csv('data\\主播数据(处理后).csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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